In recent years, there has been an increased interest in distributed artificial intelligence, and particularly in multi-agent systems (MAS) learning, such as Learning in Games [1]}. MAS further divides into competitive MAS, where agents have contradicting goals [2]}, [3]}, and cooperative MAS in which agents cooperate in order to perform some task, such as information gathering [4]}, traffic light control [5]} and navigation [6]}. Cooperative MAS have obvious advantages over single-agent approaches, as the multiple agents can share information and assume designated roles that achieve the goal in a more effective manner [7]}. It can be either centralized, in which case there is a single entity performing learning [8]}, or decentralized where there is more than one learner [9]}. While there are some environments in which a decentralized approach is preferable, there are also cases where the centralized approach is advantageous, due to the fact that the single learner has information regarding the whole system [7]}.
